Verbeke / Molenberghs Linear Mixed Models for Longitudinal Data
Erscheinungsjahr 2008
ISBN: 978-0-387-22775-7
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 568 Seiten
Reihe: Springer Series in Statistics
ISBN: 978-0-387-22775-7
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
The SAS routines on mixed models have applications in many areas of
statistics, especially biostatistics, but the procedures are not well-
documented. Based on short courses given by the authors, this book
provides practical guidance for SAS users.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Examples.- A Model for Longitudinal Data.- Exploratory Data Analysis.- Estimation of the Marginal Model.- Inference for the Marginal Model.- Inference for the Random Effects.- Fitting Linear Mixed Models with SAS.- General Guidelines for Model Building.- Exploring Serial Correlation.- Local Influence for the Linear Mixed Model.- The Heterogeneity Model.- Conditional Linear Mixed Models.- Exploring Incomplete Data.- Joint Modeling of Measurements and Missingness.- Simple Missing Data Methods.- Selection Models.- Pattern-Mixture Models.- Sensitivity Analysis for Selection Models.- Sensitivity Analysis for Pattern-Mixture Models.- How Ignorable Is Missing At Random ?.- The Expectation-Maximization Algorithm.- Design Considerations.- Case Studies.
